






import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
  from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
  import torch_xla.core.xla_model as xm

def   _lowerCamelCase						(    __A     :				Union[str, Any]			)   ->       Optional[int]:
    if is_torch_version('''<'''		,		'''2.0.0'''			) or not hasattr(__A		,		'''_dynamo'''			):
        return False
    return isinstance(__A		,		torch._dynamo.eval_frame.OptimizedModule			)

def   _lowerCamelCase						(    __A     :				Tuple		,		__A     :				bool = True			)   ->       List[str]:
    _UpperCAmelCase					:   str      	=					(torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

    _UpperCAmelCase					:   Optional[Any]      	=					is_compiled_module(__A			)
    if is_compiled:
        _UpperCAmelCase					:   Tuple      	=					model
        _UpperCAmelCase					:   Optional[int]      	=					model._orig_mod

    if is_deepspeed_available():
        options += (DeepSpeedEngine,)

    while isinstance(__A		,		__A			):
        _UpperCAmelCase					:   int      	=					model.module

    if not keep_fpaa_wrapper:
        _UpperCAmelCase					:   List[str]      	=					getattr(__A		,		'''forward'''			)
        _UpperCAmelCase					:   Optional[int]      	=					model.__dict__.pop('''_original_forward'''		,		__A			)
        if original_forward is not None:
            while hasattr(__A		,		'''__wrapped__'''			):
                _UpperCAmelCase					:   Any      	=					forward.__wrapped__
                if forward == original_forward:
                    break
            _UpperCAmelCase					:   List[str]      	=					forward
        if getattr(__A		,		'''_converted_to_transformer_engine'''		,		__A			):
            convert_model(__A		,		to_transformer_engine=__A			)

    if is_compiled:
        _UpperCAmelCase					:   int      	=					model
        _UpperCAmelCase					:   Optional[int]      	=					compiled_model

    return model

def   _lowerCamelCase						(    )   ->       Optional[Any]:
    PartialState().wait_for_everyone()

def   _lowerCamelCase						(    __A     :				str		,		__A     :				Any			)   ->       Optional[Any]:
    if PartialState().distributed_type == DistributedType.TPU:
        xm.save(__A		,		__A			)
    elif PartialState().local_process_index == 0:
        torch.save(__A		,		__A			)

@contextmanager
def   _lowerCamelCase						(    **__A     :				Optional[Any]			)   ->       int:
    for key, value in kwargs.items():
        _UpperCAmelCase					:   Optional[Any]      	=					str(__A			)

    yield

    for key in kwargs:
        if key.upper() in os.environ:
            del os.environ[key.upper()]

def   _lowerCamelCase						(    __A     :				Tuple			)   ->       str:
    if not hasattr(__A		,		'''__qualname__'''			) and not hasattr(__A		,		'''__name__'''			):
        _UpperCAmelCase					:   Union[str, Any]      	=					getattr(__A		,		'''__class__'''		,		__A			)
    if hasattr(__A		,		'''__qualname__'''			):
        return obj.__qualname__
    if hasattr(__A		,		'''__name__'''			):
        return obj.__name__
    return str(__A			)

def   _lowerCamelCase						(    __A     :				Optional[int]		,		__A     :				Union[str, Any]			)   ->       Any:
    for key, value in source.items():
        if isinstance(__A		,		__A			):
            _UpperCAmelCase					:   Tuple      	=					destination.setdefault(__A		,		{}			)
            merge_dicts(__A		,		__A			)
        else:
            _UpperCAmelCase					:   Any      	=					value

    return destination


def   _lowerCamelCase						(    __A     :				int = None			)   ->       bool:
    if port is None:
        _UpperCAmelCase					:   List[str]      	=					29_500
    with socket.socket(socket.AF_INET		,		socket.SOCK_STREAM			) as s:
        return s.connect_ex(('''localhost''', port)			) == 0












'''simple docstring'''





def __UpperCAmelCase   (					A					:			list		)    ->   list:
			if len(A		) <= 1:
						return lst

			UpperCAmelCase_      :       List[str]          =       1

			while i < len(A		):
						if lst[i - 1] <= lst[i]:
									i += 1
						else:
									UpperCAmelCase_    ,      UpperCAmelCase_      :       Dict          =       lst[i], lst[i - 1]
									i -= 1
									if i == 0:
												UpperCAmelCase_      :       Dict          =       1

			return lst


if __name__ == "__main__":
						_UpperCamelCase						:						int  =					input('Enter numbers separated by a comma:\n').strip()
						_UpperCamelCase						:						Union[str, Any]  =					[int(item) for item in user_input.split(',')]
						print(gnome_sort(unsorted))


